Integrative analysis of multi-omics data reveals links between human diseases and the gut microbiota
Doctoral thesis, 2022

The gut microbiota plays a critical role in human diseases, including type 2 diabetes (T2D) and osteoporosis. Especially, probiotics have been suggested to provide potential intervention strategies for improving human health. This thesis focuses on elucidating the interrelationships between the gut microbiota, probiotics and human diseases by integrative analysis of plasma metabolomics and gut metagenomics, using machine learning (ML) and genome-scale metabolic model (GEM). This work is mainly structured into two parts, including a systematical investigation of: (I) associations between the gut microbiota and T2D, (II) the effects of probiotic Lactobacillus reuteri ATCC PTA 6475 on bone metabolism of the elderly.   
 
For the first part, a derivative of phenylalanine was identified as a potential link between the gut microbiota and T2D. It was associated with insulin resistance and might contribute to the metabolic imbalance of (pre)diabetes. By performing a systematical analysis of four metagenomic datasets, several short-chain fatty acids (SCFAs)-producing bacteria and metabolic reactions were consistently identified to be important for predicting T2D status across different studies. For the second part, this work revealed that supplementation with L. reuteri ATCC PTA 6475 prevented detrimental alterations in the metabolisms of both the gut microbiota and the elderly as well as increased the microbial gene richness, which might link the beneficial effects of probiotic L. reuteri ATCC PTA 6475 to bone metabolism. In addition, it was demonstrated that the use of ML and GEM have the potential to identify key disease-related metabolic signatures of single L. reuteri strain, the entire gut microbes, or the human host, based on the metabolomics and metagenomics data.   
 
Taken together, this work provides novel insights into links between the gut microbiota and the human diseases as well as the positive effects of L. reuteri ATCC PTA 6475 on bone metabolism by integrating omics data using ML and GEMs.

multi-omics

gut microbiota

metabolic modeling

type 2 diabetes

machine learning

osteoporosis

metabolomics

Konferensrummet 10’an, Forskarhus 1, Kemigården 4, Chalmers
Opponent: Associate Prof. Mani Arumugam, University of Copenhagen, Denmark

Author

Peishun Li

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Machine learning for data integration in human gut microbiome

Microbial Cell Factories,; Vol. 21(2022)

Review article

Peishun Li, Boyang Ji, Dimitra Lappa, Abraham S Meijnikman, Lisa M. Olsson, Ömrüm Aydin, et.al, Thue W. Schwartz, Fredrik Bäckhed, Max Nieuwdorp, Louise E. Olofsson, Jens Nielsen. Systems analysis of metabolic responses to a mixed meal test in an obese cohort reveals links between tissue metabolism and the gut microbiota. (Under revision in Communications Medicine)

Peishun Li*, Hao Luo*, Boyang Ji and Jens Nielsen. Metagenomic analysis of type 2 diabetes datasets identifies cross-cohort microbial and metabolic signatures. (Manuscript)

Within the human intestine, a huge number of microbes live collectively, referred to as the gut microbiota. Dysbiosis of the gut microbiota has been suggested to be associated with human diseases, such as type 2 diabetes (T2D) and osteoporosis characterized by reduced bone mineral density (BMD). Moreover, growing studies have indicated that modulation of the gut microbiota, particularly oral supplementation with probiotics, could be a potential strategy for prevention and treatment of diseases.
 
This thesis mainly elucidates relationships between the gut microbiota, probiotics and human diseases by integrative analysis of plasma metabolomics and gut metagenomics, using machine learning and metabolic models. This work first systematically investigated metabolisms of both the gut microbiota and human host with (pre) diabetes. A number of gut microbial signatures, including a depleted short-chain fatty acids producing bacterial species and an enriched phenylalanine metabolism capacity of the microbiome, were identified as key factors that might contribute to T2D pathogenesis or abnormal glucose control.
 
In addition, this thesis systematically explored the effects of orally administrated Lactobacillus reuteri ATCC PTA 6475 on bone metabolism of older women with low BMD. This work found that supplementation with L. reuteri ATCC PTA 6475 had the potential to prevent a deterioration of both the gut microbiota and the host metabolism in older women. This provides a novel insight into the mechanism underlying the beneficial effects of L. reuteri ATCC PTA 6475 on metabolism of the elderly, which could be crucial for developing the novel intervention strategy of osteoporosis.

Subject Categories

Clinical Medicine

Microbiology in the medical area

Bioinformatics and Systems Biology

ISBN

978-91-7905-595-0

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5062

Publisher

Chalmers

Konferensrummet 10’an, Forskarhus 1, Kemigården 4, Chalmers

Online

Opponent: Associate Prof. Mani Arumugam, University of Copenhagen, Denmark

More information

Latest update

11/12/2023